// Reusable skill for coding agents to build RedGifs integrations, API clients, scrapers, bulk downloaders, and media tools. Incorporates the unofficial Python wrapper, auth flow, endpoints, rate-limit handling, and cross-language patterns ...
Find niches, topics, audiences, products, channels, and content angles via deep web search. Use whenever Ahmad says "find me a niche", "hunt niches in X", "what's an underserved audience for Y", "find similar sites/videos to <example>", "research the X market", "what are people building in Y space", "/niche-hunter X", or any phrasing that asks for niche / market / topic / audience / product / channel discovery across the open web. Trusts domain + keyword search; chains web_search → web_fetch / web_extract / web_crawl + reddit_search + search_youtube + github_repo_intel. NEVER uses awesome-list shortcuts. Output shape is FLEXIBLE — list, table, report, suggestions, or normal prose — picked from how Ahmad phrased the ask.
Scrub English drafts for AI tells before publishing. Use for any English LinkedIn post or newsletter draft right after composition and BEFORE export. Removes em-dash-as-pause, weak hedges, rule-of-three patterns, AI vocabulary, negative parallelisms, and inflated symbolism. Triggers on "polish", "humanize", "make this sound human", "/polisher", or after any English composer output. Leaves Arabic and Hebrew drafts untouched — humanizer-* skills handle those.
Audit a composer output against four hard checks before delivery — cite integrity, voice rules, word count, schema validity. Always invoked after the polisher (English) or humanizer-* (Arabic / Hebrew). Emits a VerificationReport Pydantic object; orchestrator branches on `overall_passed`. Target ≥0.9 score per run. Triggers automatically as the final composer sub-agent; not user-facing.
Deep research workflow that starts from a GitHub repo URL/slug, pulls upstream intel, then expands to Reddit + open web for community reception. Use whenever Ahmad gives a GitHub link and asks to understand it, see updates, audit the community, or compose a report. Trigger phrases include "research this repo", "report on this github", "what's happening upstream", "community reception", "compose a report on <repo>", and any message that contains a github.com URL plus a research/report ask.
Compose a comparison newsletter from Ahmad's OpenMark saves — A vs B vs C, side-by-side, table-driven. Use when Ahmad wants to compare tools, models, frameworks, approaches, or platforms across his saves. Trigger phrases include "compare", "X vs Y", "head to head", "which should I use", "differences between", "trade-offs between", "/newsletter-comparison". Output centers a markdown table with consistent columns, supports it with short prose blocks, ends with a clear recommendation.
Write a single-thesis narrative newsletter essay from Ahmad's OpenMark saves. Use when Ahmad wants a thoughtful long-form piece with one clear argument, not a roundup or news recap. Trigger phrases include "essay", "long-form", "think piece", "thoughtful post", "argue that", "make a case for", "/newsletter-essay". Output is one strong thesis sentence + 3–5 narrative sections + closing call-to-think, no tables, no bullets unless necessary.
| name | agent-generated-redgifs-coding-agent |
| description | Reusable skill for coding agents to build RedGifs integrations, API clients, scrapers, bulk downloaders, and media tools. Incorporates the unofficial Python wrapper, auth flow, endpoints, rate-limit handling, and cross-language patterns ... |
| metadata | {"type":"agent-generated"} |
Purpose: When the user asks you to write code involving RedGifs (searching GIFs, downloading videos, building bots, API wrappers, or media pipelines), follow this recipe exactly. Always prioritize the community-maintained redgifs Python library unless the user specifies another language.
pip install -U redgifsredgifs (https://github.com/scrazzz/redgifs {version}) Python/{pyver}.Accept: application/jsontoken from response.API.login() or use as Authorization: Bearer <token>.Example skeleton:
from redgifs import API
api = API()
api.login() # handles temporary token internally
api.search(tags="...", order=Order.TopThisWeek, count=80) → SearchResultapi.get_gif(gif_id) → GIF model with hd_url, sd_url, thumbnailapi.get_trending_gifs()api.get_top_this_week()api.search_creators(username)api.fetch_tag_suggestions(query)redgifs.aio.APIModels: GIF, Image, SearchResult, CreatorsResult, User.
Enums: Order (TopThisWeek, etc.), MediaType (g for GIF, i for image).
After install: redgifs --help or redgifs download <url or id>
Reference the gist infrastructure analysis (https://gist.github.com/devinschumacher/54e082d8bdb907aa669036cabe51634f) for:
From raw http.py: concrete routes include:
/v2/gifs/{id}/v2/gifs/search?type=g&order=...&tags=.../v2/explore/trending-gifs/v2/users/{username}/v2/niches/searchAlways include the library's UA to avoid 403s.
redgifs.aio + asyncio.gather for bulk downloads.When generating code for the user:
pip install command.If user asks for new features (e.g. niche search, creator following, custom signatures), first check the latest redgifs repo, then implement using the http.py patterns or subclass the API class.
Citations: All URLs and details above were returned by the deep research sub-agent in this session (GitHub, ReadTheDocs, PyPI, Gist, Reddit, Stack Overflow). Never invent endpoints.
This skill makes any coding agent immediately productive with RedGifs without hallucinating the auth flow or endpoints.